Split example gallery into subsections (#7849)

torchvision/transforms/v2/_augment.py

@@ -217,7 +217,7 @@ class MixUp(_BaseMixUpCutMix):
     .. note::
         This transform is meant to be used on **batches** of samples, not
         individual images. See
-        :ref:`sphx_glr_auto_examples_plot_cutmix_mixup.py` for detailed usage
+        :ref:`sphx_glr_auto_examples_v2_transforms_plot_cutmix_mixup.py` for detailed usage
         examples.
         The sample pairing is deterministic and done by matching consecutive
         samples in the batch, so the batch needs to be shuffled (this is an
@@ -267,7 +267,7 @@ class CutMix(_BaseMixUpCutMix):
     .. note::
         This transform is meant to be used on **batches** of samples, not
         individual images. See
-        :ref:`sphx_glr_auto_examples_plot_cutmix_mixup.py` for detailed usage
+        :ref:`sphx_glr_auto_examples_v2_transforms_plot_cutmix_mixup.py` for detailed usage
         examples.
         The sample pairing is deterministic and done by matching consecutive
         samples in the batch, so the batch needs to be shuffled (this is an

torchvision/transforms/v2/functional/_utils.py

@@ -69,7 +69,7 @@ _BUILTIN_DATAPOINT_TYPES = {
 def register_kernel(functional, datapoint_cls):
     """Decorate a kernel to register it for a functional and a (custom) datapoint type.
 
-    See :ref:`sphx_glr_auto_examples_plot_custom_datapoints.py` for usage
+    See :ref:`sphx_glr_auto_examples_v2_transforms_plot_custom_datapoints.py` for usage
     details.
     """
     if isinstance(functional, str):